Lagrangian Dynamics and Simulation-Based PID Control of a Two-Joint Lower-Limb Exoskeleton Robot

International Journal of Electronics and Communication Engineering
© 2026 by SSRG - IJECE Journal
Volume 13 Issue 2
Year of Publication : 2026
Authors : Thi-Mai-Phuong Dao, Van-Nam Vu, Kim-An Hoang, Tuan-Dat Nguyen, Ngoc-Khoat Nguyen, Tien-Loc Le, Tien-Dung Nguyen, Thi-Kim-Thanh Tran
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Thi-Mai-Phuong Dao, Van-Nam Vu, Kim-An Hoang, Tuan-Dat Nguyen, Ngoc-Khoat Nguyen, Tien-Loc Le, Tien-Dung Nguyen, Thi-Kim-Thanh Tran, "Lagrangian Dynamics and Simulation-Based PID Control of a Two-Joint Lower-Limb Exoskeleton Robot," SSRG International Journal of Electronics and Communication Engineering, vol. 13,  no. 2, pp. 147-157, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I2P111

Abstract:

Lower-limb exoskeleton robots are used for functional recovery and for supporting people in physical activities. In this study, a PID controller is designed and simulated for a lower-limb exoskeleton system to support the flexion and extension of the hip and knee joints. First, the nonlinear dynamic model of the Exoskeleton is derived using the Lagrangian method. This model is then used to design the controller. The PID parameters are tuned using simulations in MATLAB/Simulink. The performance of the system is evaluated by percent Overshoot (%OS), Settling Time (Ts), and Root Mean Square Error (RMSE) in trajectory tracking. The simulation results show that the PID controller can follow the desired trajectories with acceptable accuracy, and the system remains stable. The steady-state error is small, and the transient response is acceptable for basic practical operation. From the simulation results, PID control can be applied to the Real-Time Control of a 2-DOF Exoskeleton System. This study can also be used as a reference for future studies on Exoskeleton Systems with more degrees of freedom and for applying other strategies such as fuzzy-PID and Sliding Mode Control (SMC).

Keywords:

Lower-limb Exoskeleton, PID controller, Lagrangian model, MATLAB/Simulink simulation, Trajectory tracking.

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